Details

Autor(en) / Beteiligte

• Radoux, Julien
• Chome, Guillaume
• Jacques, Damien Christophe
• Waldner, Francois
• Bellemans, Nicolas
• Matton, Nicolas
• Lamarche, Celine
• d'Andrimont, Raphaeel
• Defourny, Pierre

Titel

Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

Ist Teil von

• Remote sensing (Basel, Switzerland), 2016, Vol.8 (6), p.488-488

Ort / Verlag

MDPI AG

Erscheinungsjahr

2016

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Land cover and land use maps derived from satellite remote sensing imagery are critical to support biodiversity and conservation, especially over large areas. With its 10 m to 20 m spatial resolution, Sentinel-2 is a promising sensor for the detection of a variety of landscape features of ecological relevance. However, many components of the ecological network are still smaller than the 10 m pixel, i.e., they are sub-pixel targets that stretch the sensor's resolution to its limit. This paper proposes a framework to empirically estimate the minimum object size for an accurate detection of a set of structuring landscape foreground/background pairs. The developed method combines a spectral separability analysis and an empirical point spread function estimation for Sentinel-2. The same approach was also applied to Landsat-8 and SPOT-5 (Take 5), which can be considered as similar in terms of spectral definition and spatial resolution, respectively. Results show that Sentinel-2 performs consistently on both aspects. A large number of indices have been tested along with the individual spectral bands and target discrimination was possible in all but one case. Overall, results for Sentinel-2 highlight the critical importance of a good compromise between the spatial and spectral resolution. For instance, the Sentinel-2 roads detection limit was of 3 m and small water bodies are separable with a diameter larger than 11 m. In addition, the analysis of spectral mixtures draws attention to the uneven sensitivity of a variety of spectral indices. The proposed framework could be implemented to assess the fitness for purpose of future sensors within a large range of applications.